Probabilistic logic learning
نویسندگان
چکیده
منابع مشابه
Knowledge-Based Probabilistic Logic Learning
Advice giving has been long explored in artificial intelligence to build robust learning algorithms. We consider advice giving in relational domains where the noise is systematic. The advice is provided as logical statements that are then explicitly considered by the learning algorithm at every update. Our empirical evidence proves that human advice can effectively accelerate learning in noisy ...
متن کاملCHR(PRISM)-based probabilistic logic learning
PRISM is an extension of Prolog with probabilistic predicates and built-in support for expectation-maximization learning. Constraint Handling Rules (CHR) is a high-level programming language based on multi-headed multiset rewrite rules. In this paper, we introduce a new probabilistic logic formalism, called CHRiSM, based on a combination of CHR and PRISM. It can be used for high-level rapid pro...
متن کاملLearning Probabilistic Logic Models with Human Advice
We consider the problem of interactive machine learning for rich, structured and noisy domains. We present a recently successful learning algorithm and provide several extensions for incorporating rich, high level, human feedback. We then discuss some open problems in this area.
متن کاملLearning the Structure of Probabilistic Logic Programs
There is a growing interest in the field of Probabilistic Inductive Logic Programming, which uses languages that integrate logic programming and probability. Many of these languages are based on the distribution semantics and recently various authors have proposed systems for learning the parameters (PRISM, LeProbLog, LFI-ProbLog and EMBLEM) or both the structure and the parameters (SEM-CP-logi...
متن کاملLifted Discriminative Learning of Probabilistic Logic Programs
Probabilistic logic programming (PLP) provides a powerful tool for reasoning with uncertain relational models. However, learning probabilistic logic programs is expensive due to the high cost of inference. Among the proposals to overcome this problem, one of the most promising is lifted inference. In this paper we consider PLP models that are amenable to lifted inference and present an algorith...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ACM SIGKDD Explorations Newsletter
سال: 2003
ISSN: 1931-0145,1931-0153
DOI: 10.1145/959242.959247